Facial Expression Prediction: Same trend can be observed in facial expression prediction similar to video representation. At first, hand-crafted and geometrical features are used to predict emotions from images/videos [1]}, [2]}. Later, deep learning techniques are applied to obtain more robust visual descriptions [3]}, [4]}, [5]}, [6]}. However, the limited number of training samples is a major concern on this domain. Thus, studies are usually concentrated on transfer learning and data augmentation to extract reliable deep features by adapting pretrained models to the problem [3]}, [4]}. Also, video-level representation can be obtained by considering simple feature distribution characteristics in time (i.e. mean and variance) [5]} as well as by common pooling techniques.
